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8 data strategy mistakes to avoid

CIO Business Intelligence

“Similar to disaster recovery, business continuity, and information security, data strategy needs to be well thought out and defined to inform the rest, while providing a foundation from which to build a strong business.” Overlooking these data resources is a big mistake. What are the goals for leveraging unstructured data?”

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Mastering Data Analysis Report and Dashboard

FineReport

Data Analysis Report (by FineReport ) Note: All the data analysis reports in this article are created using the FineReport reporting tool. Leveraging the advanced enterprise-level web reporting tool capabilities of FineReport , we empower businesses to achieve genuine data transformation. Try FineReport Now 1.

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How to Include BI in Your 2020 Budget

Sisense

Yet with this surge in data, many organizations are either not able to draw insights from their data, or are not able to do so quickly enough. It is estimated that of all data collected, less than 1% is actually analyzed and used. Your data is a gold mine and you’re barely scratching the surface of its value!

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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science.

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Addressing the Three Scalability Challenges in Modern Data Platforms

Cloudera

Open source frameworks such as Apache Impala, Apache Hive and Apache Spark offer a highly scalable programming model that is capable of processing massive volumes of structured and unstructured data by means of parallel execution on a large number of commodity computing nodes. .

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What is a Data Pipeline?

Jet Global

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.